Authorship Poll Analysis
Meghan Duffy
June 15, 2016
What are the current views on last and corresponding authorship in ecology?
Introduction
Who is the last author on a paper? Is it the person who did the least work? Or is it the PI of the lab where the work was done? When I started grad school (in 2000), the norm in ecology was still that the last author on a paper is the person who did the least work. But, more recently, it has seemed to me that the norm is that the last author on a paper is the “senior” author (usually the PI). However, if you talk with other ecologists about the topic, it’s clear that there’s variation in views, and that not everyone is on the same page.
This project started out as a poll on the Dynamic Ecology blog, but has led to a bigger project. The code here has been updated to reflect what is in the manuscript on this (in revision for Ecology & Evolution), rather than the original blog posts.
Literature review
I used a combination of Web of Science data and manually searching through journals to determine the number of authors and corresponding authorship for papers in Ecology from 1956-2016 (every 10 years from 1956-1996, every five years from 2001-2016) and in American Naturalist, Evolution, and Oikos in 2001, 2006, 2011, and 2016.
Making figures and doing analyses for revised version of manuscript (incorporating suggestions from the reviewers)
##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union##
## Attaching package: 'cowplot'## The following object is masked from 'package:ggplot2':
##
## ggsave
##
## Call:
## glm(formula = numberauthors ~ Year, family = poisson(), data = ecologyWoSdata)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.9081 -0.6508 -0.1922 0.3472 8.5998
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -47.87826 2.00366 -23.89 <2e-16 ***
## Year 0.02447 0.00100 24.46 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 2531.1 on 1911 degrees of freedom
## Residual deviance: 1822.8 on 1910 degrees of freedom
## AIC: 7146
##
## Number of Fisher Scoring iterations: 5##
## Call:
## glm(formula = numberauthors ~ Year + Journal + Year * Journal,
## family = poisson(), data = recentWoSdata)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.0500 -0.7499 -0.3020 0.3934 8.6805
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -46.747359 8.743948 -5.346 8.98e-08 ***
## Year 0.023834 0.004351 5.477 4.31e-08 ***
## JournalEcology -22.925916 10.334102 -2.218 0.0265 *
## JournalEvolution -12.202433 10.870768 -1.122 0.2617
## JournalOikos -23.118439 11.177112 -2.068 0.0386 *
## Year:JournalEcology 0.011487 0.005142 2.234 0.0255 *
## Year:JournalEvolution 0.006102 0.005410 1.128 0.2593
## Year:JournalOikos 0.011539 0.005563 2.074 0.0380 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 4078.2 on 3619 degrees of freedom
## Residual deviance: 3647.5 on 3612 degrees of freedom
## AIC: 14369
##
## Number of Fisher Scoring iterations: 5## Analysis of Deviance Table
##
## Model 1: numberauthors ~ Year + Journal + Year * Journal
## Model 2: numberauthors ~ Year + Journal
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 3612 3647.5
## 2 3615 3653.8 -3 -6.3166 0.09718 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Analysis of Deviance Table
##
## Model 1: numberauthors ~ Year
## Model 2: numberauthors ~ Year + Journal
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 3618 3692.8
## 2 3615 3653.8 3 39.014 1.724e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Analysis of Deviance Table
##
## Model 1: numberauthors ~ Journal
## Model 2: numberauthors ~ Year + Journal
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 3616 4038.2
## 2 3615 3653.8 1 384.34 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## # A tibble: 9 x 3
## Year `median(numberauthors)` `mean(numberauthors)`
## <int> <dbl> <dbl>
## 1 1956 1 1.378049
## 2 1966 1 1.517241
## 3 1976 1 1.663934
## 4 1986 2 1.756250
## 5 1996 2 2.292887
## 6 2001 2 2.688406
## 7 2006 3 3.255255
## 8 2011 3 4.030435
## 9 2016 4 4.566154## # A tibble: 5 x 3
## Correspondence n rel.freq
## <fctr> <int> <dbl>
## 1 all 2 0
## 2 first 751 84
## 3 last 114 13
## 4 middle 16 2
## 5 other 8 1## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
##
## Call:
## glm(formula = Cor01 ~ Year + Journal + Year * Journal, family = binomial(),
## data = recentWoSdataCor)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.0991 0.4838 0.5142 0.5975 1.4107
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.910e+02 4.327e+01 -4.414 1.02e-05 ***
## Year 9.568e-02 2.154e-02 4.442 8.93e-06 ***
## JournalEcology 1.494e+02 5.773e+01 2.587 0.00967 **
## JournalEvolution -1.156e+01 5.308e+01 -0.218 0.82764
## JournalOikos 1.823e+02 6.395e+01 2.851 0.00436 **
## Year:JournalEcology -7.406e-02 2.873e-02 -2.578 0.00994 **
## Year:JournalEvolution 5.281e-03 2.642e-02 0.200 0.84158
## Year:JournalOikos -9.034e-02 3.183e-02 -2.838 0.00454 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 3159.0 on 2984 degrees of freedom
## Residual deviance: 2841.7 on 2977 degrees of freedom
## AIC: 2857.7
##
## Number of Fisher Scoring iterations: 4## Analysis of Deviance Table
##
## Model 1: Cor01 ~ Year + Journal + Year * Journal
## Model 2: Cor01 ~ Year + Journal
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 2977 2841.7
## 2 2980 2861.1 -3 -19.344 0.0002321 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Analysis of Deviance Table
##
## Model 1: Cor01 ~ Year
## Model 2: Cor01 ~ Year + Journal
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 2983 3119.9
## 2 2980 2861.1 3 258.88 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Analysis of Deviance Table
##
## Model 1: Cor01 ~ Journal
## Model 2: Cor01 ~ Year + Journal
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 2981 2909.1
## 2 2980 2861.1 1 48.013 4.235e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1##
## Call:
## glm(formula = LastCor01 ~ Year + Journal + Year * Journal, family = binomial(),
## data = recentWoSdataCor)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.6107 -0.4933 -0.4215 -0.3799 2.4560
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.347e+02 6.808e+01 -1.978 0.0479 *
## Year 6.585e-02 3.384e-02 1.946 0.0517 .
## JournalEcology 2.592e+00 8.324e+01 0.031 0.9752
## JournalEvolution -5.252e+01 8.458e+01 -0.621 0.5346
## JournalOikos 1.065e+02 8.711e+01 1.222 0.2217
## Year:JournalEcology -1.291e-03 4.138e-02 -0.031 0.9751
## Year:JournalEvolution 2.623e-02 4.205e-02 0.624 0.5328
## Year:JournalOikos -5.299e-02 4.332e-02 -1.223 0.2213
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1889.7 on 2984 degrees of freedom
## Residual deviance: 1859.0 on 2977 degrees of freedom
## AIC: 1875
##
## Number of Fisher Scoring iterations: 5## Analysis of Deviance Table
##
## Model 1: LastCor01 ~ Year + Journal + Year * Journal
## Model 2: LastCor01 ~ Year + Journal
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 2977 1859.0
## 2 2980 1863.8 -3 -4.7582 0.1904## Analysis of Deviance Table
##
## Model 1: LastCor01 ~ Year
## Model 2: LastCor01 ~ Year + Journal
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 2983 1867.4
## 2 2980 1863.8 3 3.6155 0.3061## Analysis of Deviance Table
##
## Model 1: LastCor01 ~ Journal
## Model 2: LastCor01 ~ Year + Journal
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 2981 1885.7
## 2 2980 1863.8 1 21.929 2.829e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## # A tibble: 11 x 4
## # Groups: Region [6]
## Region LastCor01 n rel.freq
## <fctr> <dbl> <int> <dbl>
## 1 Africa 0 10 100
## 2 Asia 0 33 63
## 3 Asia 1 19 37
## 4 Europe 0 255 86
## 5 Europe 1 41 14
## 6 North America 0 398 91
## 7 North America 1 40 9
## 8 Oceania 0 60 86
## 9 Oceania 1 10 14
## 10 South America 0 21 84
## 11 South America 1 4 16## # A tibble: 11 x 4
## # Groups: Region [6]
## Region Cor01 n rel.freq
## <fctr> <dbl> <int> <dbl>
## 1 Africa 1 10 100
## 2 Asia 0 22 42
## 3 Asia 1 30 58
## 4 Europe 0 49 17
## 5 Europe 1 247 83
## 6 North America 0 53 12
## 7 North America 1 385 88
## 8 Oceania 0 11 16
## 9 Oceania 1 59 84
## 10 South America 0 6 24
## 11 South America 1 19 76
##
## Call:
## glm(formula = LastCor01 ~ Region, family = binomial(link = logit),
## data = WoSdata2016EurNA)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.5461 -0.5461 -0.4376 -0.4376 2.1879
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.8277 0.1683 -10.862 <2e-16 ***
## RegionNorth America -0.4699 0.2363 -1.989 0.0467 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 509.77 on 733 degrees of freedom
## Residual deviance: 505.83 on 732 degrees of freedom
## AIC: 509.83
##
## Number of Fisher Scoring iterations: 5##
## Call:
## glm(formula = Cor01 ~ Region, family = binomial(link = logit),
## data = WoSdata2016EurNA)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.0552 0.5079 0.5079 0.6016 0.6016
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.6176 0.1564 10.343 <2e-16 ***
## RegionNorth America 0.3654 0.2143 1.705 0.0882 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 591.72 on 733 degrees of freedom
## Residual deviance: 588.83 on 732 degrees of freedom
## AIC: 592.83
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = LastCor01 ~ Region, family = binomial(link = logit),
## data = WoSdata2016RegionsEnough)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.9537 -0.5461 -0.4376 -0.4376 2.1879
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.5521 0.2880 -1.917 0.055236 .
## RegionEurope -1.2756 0.3335 -3.825 0.000131 ***
## RegionNorth America -1.7455 0.3323 -5.252 1.5e-07 ***
## RegionOceania -1.2397 0.4468 -2.775 0.005524 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 656.61 on 855 degrees of freedom
## Residual deviance: 631.52 on 852 degrees of freedom
## AIC: 639.52
##
## Number of Fisher Scoring iterations: 5##
## Call:
## glm(formula = Cor01 ~ Region, family = binomial(link = logit),
## data = WoSdata2016RegionsEnough)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.0552 0.5079 0.5079 0.6016 1.0489
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.3102 0.2807 1.105 0.26917
## RegionEurope 1.3074 0.3213 4.069 4.72e-05 ***
## RegionNorth America 1.6728 0.3166 5.283 1.27e-07 ***
## RegionOceania 1.3695 0.4320 3.170 0.00152 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 746.18 on 855 degrees of freedom
## Residual deviance: 720.57 on 852 degrees of freedom
## AIC: 728.57
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = Cor01 ~ ordered(binnedauthors), family = binomial(link = "logit"),
## data = WoSdata2016RegionsNot1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.2101 0.4880 0.5729 0.6681 0.8257
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 3.12201 48.75779 0.064 0.949
## ordered(binnedauthors).L 7.18002 226.60539 0.032 0.975
## ordered(binnedauthors).Q 7.80157 233.37106 0.033 0.973
## ordered(binnedauthors).C 6.67405 195.25234 0.034 0.973
## ordered(binnedauthors)^4 3.68644 137.30401 0.027 0.979
## ordered(binnedauthors)^5 2.19802 81.13878 0.027 0.978
## ordered(binnedauthors)^6 0.57633 39.44861 0.015 0.988
## ordered(binnedauthors)^7 0.17907 14.98395 0.012 0.990
## ordered(binnedauthors)^8 -0.01144 3.87615 -0.003 0.998
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 761.25 on 842 degrees of freedom
## Residual deviance: 743.49 on 834 degrees of freedom
## AIC: 761.49
##
## Number of Fisher Scoring iterations: 14##
## Call:
## glm(formula = LastCor01 ~ ordered(binnedauthors), family = binomial(link = "logit"),
## data = WoSdata2016RegionsNot1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.6681 -0.5815 -0.5389 -0.4516 2.2101
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -3.346513 48.757801 -0.069 0.945
## ordered(binnedauthors).L -7.054922 226.605421 -0.031 0.975
## ordered(binnedauthors).Q -7.573393 233.371092 -0.032 0.974
## ordered(binnedauthors).C -6.418017 195.252382 -0.033 0.974
## ordered(binnedauthors)^4 -3.801151 137.304047 -0.028 0.978
## ordered(binnedauthors)^5 -2.305563 81.138836 -0.028 0.977
## ordered(binnedauthors)^6 -0.726725 39.448764 -0.018 0.985
## ordered(binnedauthors)^7 -0.353257 14.984429 -0.024 0.981
## ordered(binnedauthors)^8 -0.002962 3.877852 -0.001 0.999
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 668.01 on 842 degrees of freedom
## Residual deviance: 658.55 on 834 degrees of freedom
## AIC: 676.55
##
## Number of Fisher Scoring iterations: 14##
## Call:
## glm(formula = Cor01 ~ ordered(binnedauthors7), family = binomial(link = "logit"),
## data = WoSdata2016RegionsNot1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.0915 0.4880 0.5729 0.6559 0.7225
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.55345 0.09442 16.452 <2e-16 ***
## ordered(binnedauthors7).L -0.58424 0.23106 -2.528 0.0115 *
## ordered(binnedauthors7).Q 0.32459 0.22584 1.437 0.1506
## ordered(binnedauthors7).C 0.07147 0.23535 0.304 0.7614
## ordered(binnedauthors7)^4 0.09013 0.23660 0.381 0.7033
## ordered(binnedauthors7)^5 0.03278 0.22737 0.144 0.8854
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 761.25 on 842 degrees of freedom
## Residual deviance: 752.61 on 837 degrees of freedom
## AIC: 764.61
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = LastCor01 ~ ordered(binnedauthors7), family = binomial(link = "logit"),
## data = WoSdata2016RegionsNot1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.6216 -0.5601 -0.5389 -0.4516 2.1604
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.81604 0.10330 -17.580 <2e-16 ***
## ordered(binnedauthors7).L 0.40227 0.25239 1.594 0.111
## ordered(binnedauthors7).Q -0.29073 0.24791 -1.173 0.241
## ordered(binnedauthors7).C -0.03314 0.25671 -0.129 0.897
## ordered(binnedauthors7)^4 -0.14677 0.25806 -0.569 0.570
## ordered(binnedauthors7)^5 0.02015 0.24997 0.081 0.936
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 668.01 on 842 degrees of freedom
## Residual deviance: 663.76 on 837 degrees of freedom
## AIC: 675.76
##
## Number of Fisher Scoring iterations: 4
## # A tibble: 10 x 2
## binnedauthors n
## <fctr> <int>
## 1 1 48
## 2 10+ 45
## 3 2 196
## 4 3 185
## 5 4 150
## 6 5 114
## 7 6 74
## 8 7 45
## 9 8 23
## 10 9 11## # A tibble: 10 x 2
## binnedauthors n
## <fctr> <int>
## 1 1 48
## 2 10+ 45
## 3 2 196
## 4 3 185
## 5 4 150
## 6 5 114
## 7 6 74
## 8 7 45
## 9 8 23
## 10 9 11## # A tibble: 18 x 4
## # Groups: binnedauthors [10]
## binnedauthors LastCor01 n rel.freq
## <fctr> <dbl> <int> <dbl>
## 1 1 0 48 100
## 2 10+ 0 38 84
## 3 10+ 1 7 16
## 4 2 0 177 90
## 5 2 1 19 10
## 6 3 0 160 86
## 7 3 1 25 14
## 8 4 0 129 86
## 9 4 1 21 14
## 10 5 0 96 84
## 11 5 1 18 16
## 12 6 0 61 82
## 13 6 1 13 18
## 14 7 0 36 80
## 15 7 1 9 20
## 16 8 0 21 91
## 17 8 1 2 9
## 18 9 0 11 100## # A tibble: 18 x 4
## # Groups: binnedauthors [10]
## binnedauthors Cor01 n rel.freq
## <fctr> <dbl> <int> <dbl>
## 1 1 1 48 100
## 2 10+ 0 9 20
## 3 10+ 1 36 80
## 4 2 0 22 11
## 5 2 1 174 89
## 6 3 0 28 15
## 7 3 1 157 85
## 8 4 0 27 18
## 9 4 1 123 82
## 10 5 0 23 20
## 11 5 1 91 80
## 12 6 0 17 23
## 13 6 1 57 77
## 14 7 0 13 29
## 15 7 1 32 71
## 16 8 0 2 9
## 17 8 1 21 91
## 18 9 1 11 100## # A tibble: 13 x 4
## # Groups: binnedauthors7 [7]
## binnedauthors7 LastCor01 n rel.freq
## <fctr> <dbl> <int> <dbl>
## 1 1 0 48 100
## 2 2 0 177 90
## 3 2 1 19 10
## 4 3 0 160 86
## 5 3 1 25 14
## 6 4 0 129 86
## 7 4 1 21 14
## 8 5 0 96 84
## 9 5 1 18 16
## 10 6 0 61 82
## 11 6 1 13 18
## 12 7+ 0 106 85
## 13 7+ 1 18 15## # A tibble: 13 x 4
## # Groups: binnedauthors7 [7]
## binnedauthors7 Cor01 n rel.freq
## <fctr> <dbl> <int> <dbl>
## 1 1 1 48 100
## 2 2 0 22 11
## 3 2 1 174 89
## 4 3 0 28 15
## 5 3 1 157 85
## 6 4 0 27 18
## 7 4 1 123 82
## 8 5 0 23 20
## 9 5 1 91 80
## 10 6 0 17 23
## 11 6 1 57 77
## 12 7+ 0 24 19
## 13 7+ 1 100 81
The poll
The poll had four main questions:
- For ecology papers, do you consider the last author to be the senior author?
- Which of the following statements most closely matches the current norms in ecology in terms of who is corresponding author?
- Which of the following statements would be best practice in terms of who is corresponding author?
- If someone includes a statement on his/her CV indicating they have used a first/last author emphasis, do you pay attention to that?
It also asked about the respondent’s primary research area, whether their research is primarily basic or applied, how frequently they conduct interdisciplinary research, how many years post-PhD they are, where they live, and what their current department is.
The poll first appeared on 6 April 2016 and ran for two weeks.
Basic overview of responses
After removing the four blank responses, there were 1122 responses to the poll. What did the respondents look like?
| PrimaryResearch | n | rel.freq |
|---|---|---|
| Biology other than EEB | 24 | 2 |
| Ecology (primarily computational-based) | 217 | 19 |
| Ecology (primarily field-based) | 558 | 50 |
| Ecology (primarily wet-lab based, including molecular ecology) | 119 | 11 |
| Evolutionary biology (primarily molecular) | 51 | 5 |
| Evolutionary biology (primarily organismal) | 130 | 12 |
| Outside biology | 21 | 2 |
| BasicApplied | n | rel.freq |
|---|---|---|
| Applied | 362 | 33 |
| Basic | 751 | 67 |
| Interdisciplinary | n | rel.freq |
|---|---|---|
| Always | 50 | 4 |
| Often | 271 | 24 |
| Sometimes | 401 | 36 |
| Rarely | 293 | 26 |
| Never | 99 | 9 |
| YearssincePhD | n | rel.freq |
|---|---|---|
| 0 (current students should choose this) | 311 | 28 |
| 5-Jan | 344 | 31 |
| 10-Jun | 200 | 18 |
| 15-Nov | 136 | 12 |
| 16-20 | 57 | 5 |
| >20 | 53 | 5 |
| I do not have a PhD and am not a current student | 20 | 2 |
| WhereLive | n | rel.freq |
|---|---|---|
| Africa | 8 | 1 |
| Asia | 13 | 1 |
| Australia | 63 | 6 |
| Europe | 288 | 26 |
| North America | 717 | 64 |
| South America | 30 | 3 |
| Dept01 | n | rel.freq |
|---|---|---|
| 1 | 304 | 28 |
| 2 | 444 | 41 |
| 3 | 212 | 19 |
| 4 | 134 | 12 |
Results for the four main questions
Q1: “For ecology papers, do you consider the last author to be the senior author?”
## # A tibble: 6 x 3
## LastSenior01 n rel.freq
## <int> <int> <dbl>
## 1 1 77 7
## 2 2 61 5
## 3 3 19 2
## 4 4 88 8
## 5 5 395 35
## 6 6 480 43## [1] 1 2 3 4 5 6
## Levels: 1 2 3 4 5 6
Q3: “Which of the following statements would be best practice in terms of who is corresponding author?”
## # A tibble: 5 x 3
## CorrespondingBest01 n rel.freq
## <int> <int> <dbl>
## 1 1 266 24
## 2 2 40 4
## 3 3 84 8
## 4 4 46 4
## 5 5 676 61
Q4: “If someone includes a statement on his/her CV indicating they have used a first/last author emphasis, do you pay attention to that?”
## # A tibble: 4 x 3
## CVStatement01 n rel.freq
## <int> <int> <dbl>
## 1 1 87 8
## 2 2 234 21
## 3 3 538 49
## 4 4 245 22
Looking at cross-tabs
Does whether people view the last author as the senior author vary based on age, country, research area, and/or department?
## Scale for 'y' is already present. Adding another scale for 'y', which
## will replace the existing scale.
## Scale for 'y' is already present. Adding another scale for 'y', which
## will replace the existing scale.
## Scale for 'y' is already present. Adding another scale for 'y', which
## will replace the existing scale.
## Scale for 'y' is already present. Adding another scale for 'y', which
## will replace the existing scale.
##
## Call:
## glm(formula = LastSeniorYes ~ ordered(PhD01), family = binomial(link = "logit"),
## data = polldatacareerstageanalysis)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.8519 0.6300 0.6527 0.6608 0.8758
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.19334 0.09081 13.142 <2e-16 ***
## ordered(PhD01).L -0.51899 0.23563 -2.203 0.0276 *
## ordered(PhD01).Q -0.05427 0.21699 -0.250 0.8025
## ordered(PhD01).C 0.13817 0.23170 0.596 0.5510
## ordered(PhD01)^4 -0.20785 0.22774 -0.913 0.3614
## ordered(PhD01)^5 -0.43600 0.19804 -2.202 0.0277 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1140.7 on 1098 degrees of freedom
## Residual deviance: 1127.4 on 1093 degrees of freedom
## (2 observations deleted due to missingness)
## AIC: 1139.4
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = LastSeniorYes ~ factor(PhD01), family = binomial(link = "logit"),
## data = polldatacareerstageanalysis)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.8519 0.6300 0.6527 0.6608 0.8758
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.41059 0.14281 9.878 < 2e-16 ***
## factor(PhD01)2 0.02738 0.19784 0.138 0.88993
## factor(PhD01)3 0.10576 0.23296 0.454 0.64983
## factor(PhD01)4 -0.65000 0.23349 -2.784 0.00537 **
## factor(PhD01)5 -0.21434 0.34724 -0.617 0.53706
## factor(PhD01)6 -0.57226 0.33154 -1.726 0.08434 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1140.7 on 1098 degrees of freedom
## Residual deviance: 1127.4 on 1093 degrees of freedom
## (2 observations deleted due to missingness)
## AIC: 1139.4
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = LastSeniorYes ~ PhD01, family = binomial(link = "logit"),
## data = polldatacareerstageanalysis)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.8473 0.6330 0.6713 0.7114 0.8424
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.63639 0.15318 10.683 <2e-16 ***
## PhD01 -0.13049 0.05096 -2.561 0.0104 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1140.7 on 1098 degrees of freedom
## Residual deviance: 1134.3 on 1097 degrees of freedom
## (2 observations deleted due to missingness)
## AIC: 1138.3
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = LastSeniorYes ~ WhereLive, family = binomial(link = "logit"),
## data = polldatawhereliveanalysis)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.1114 0.4773 0.7860 0.7860 0.7860
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 2.1151 0.1901 11.125 < 2e-16 ***
## WhereLiveNorth America -1.0987 0.2081 -5.279 1.3e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1057.8 on 1002 degrees of freedom
## Residual deviance: 1024.7 on 1001 degrees of freedom
## (2 observations deleted due to missingness)
## AIC: 1028.7
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = LastSeniorYes ~ ecoevo, family = binomial(link = "logit"),
## data = polldataecoevoanalysis)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.2563 0.4042 0.7282 0.7282 0.7282
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.19188 0.07917 15.055 <2e-16 ***
## ecoevoevolution 1.27197 0.52649 2.416 0.0157 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1005.62 on 943 degrees of freedom
## Residual deviance: 997.45 on 942 degrees of freedom
## (1 observation deleted due to missingness)
## AIC: 1001.5
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = LastSeniorYes ~ factor(Dept01), family = binomial(link = "logit"),
## data = polldata)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.8691 0.6190 0.6319 0.6319 0.8672
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.55516 0.15117 10.288 < 2e-16 ***
## factor(Dept01)2 -0.04554 0.19523 -0.233 0.81554
## factor(Dept01)3 -0.64876 0.21417 -3.029 0.00245 **
## factor(Dept01)4 -0.77104 0.23986 -3.215 0.00131 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1139.9 on 1091 degrees of freedom
## Residual deviance: 1120.5 on 1088 degrees of freedom
## (30 observations deleted due to missingness)
## AIC: 1128.5
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = LastSeniorYes ~ BasicApplied, family = binomial(link = "logit"),
## data = polldata)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.7721 0.6829 0.6829 0.6829 0.7377
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.1624 0.1235 9.409 <2e-16 ***
## BasicAppliedBasic 0.1746 0.1528 1.142 0.253
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1164.6 on 1110 degrees of freedom
## Residual deviance: 1163.3 on 1109 degrees of freedom
## (11 observations deleted due to missingness)
## AIC: 1167.3
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = LastSeniorYes ~ ordered(Inter01), family = binomial(link = "logit"),
## data = polldata)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.8170 0.6528 0.6813 0.6856 0.7760
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.25438 0.09486 13.223 <2e-16 ***
## ordered(Inter01).L -0.32772 0.26780 -1.224 0.221
## ordered(Inter01).Q -0.03991 0.23564 -0.169 0.866
## ordered(Inter01).C 0.03625 0.18232 0.199 0.842
## ordered(Inter01)^4 0.07303 0.13962 0.523 0.601
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1167.7 on 1111 degrees of freedom
## Residual deviance: 1164.8 on 1107 degrees of freedom
## (10 observations deleted due to missingness)
## AIC: 1174.8
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = LastSeniorYes ~ factor(PhD01) + WhereLive + ecoevo +
## factor(Dept01) + BasicApplied + factor(Inter01), family = binomial(link = "logit"),
## data = polldata)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.6847 0.3759 0.5753 0.7159 1.4114
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 2.53419 1.16597 2.173 0.0297 *
## factor(PhD01)2 -0.04062 0.21102 -0.193 0.8473
## factor(PhD01)3 0.07253 0.25733 0.282 0.7780
## factor(PhD01)4 -0.64578 0.26045 -2.480 0.0132 *
## factor(PhD01)5 -0.29355 0.36578 -0.803 0.4222
## factor(PhD01)6 -0.74529 0.36574 -2.038 0.0416 *
## factor(PhD01)7 -1.15988 0.52485 -2.210 0.0271 *
## WhereLiveAsia -0.08813 1.53803 -0.057 0.9543
## WhereLiveAustralia -0.52962 1.17525 -0.451 0.6522
## WhereLiveEurope -0.06630 1.13870 -0.058 0.9536
## WhereLiveNorth America -1.14142 1.12360 -1.016 0.3097
## WhereLiveSouth America -0.59004 1.21063 -0.487 0.6260
## ecoevoevolution 1.25612 0.53976 2.327 0.0200 *
## ecoevoother 0.42611 0.23144 1.841 0.0656 .
## factor(Dept01)2 0.01599 0.20737 0.077 0.9385
## factor(Dept01)3 -0.50289 0.23717 -2.120 0.0340 *
## factor(Dept01)4 -0.68132 0.26610 -2.560 0.0105 *
## BasicAppliedBasic -0.08662 0.18043 -0.480 0.6312
## factor(Inter01)2 -0.07559 0.31413 -0.241 0.8098
## factor(Inter01)3 -0.02043 0.30706 -0.067 0.9469
## factor(Inter01)4 -0.08176 0.32469 -0.252 0.8012
## factor(Inter01)5 -0.14310 0.44539 -0.321 0.7480
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1119.7 on 1076 degrees of freedom
## Residual deviance: 1043.6 on 1055 degrees of freedom
## (45 observations deleted due to missingness)
## AIC: 1087.6
##
## Number of Fisher Scoring iterations: 5Does whether people pay attention to a CV statement vary based on age, country, research area, department and/or their views on last authorship?
## [1] "Biology other than EEB"
## [2] "Ecology (primarily computational-based)"
## [3] "Ecology (primarily field-based)"
## [4] "Ecology (primarily wet-lab based, including molecular ecology)"
## [5] "Evolutionary biology (primarily molecular)"
## [6] "Evolutionary biology (primarily organismal)"
## [7] "Outside biology"
Do views on corresponding authorship vary based on age, country, research area, and/or department?
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
##
## Call:
## glm(formula = FullResYes ~ ordered(PhD01), family = binomial(link = "logit"),
## data = polldatacareerstageanalysis2)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.341 -1.235 1.022 1.121 1.226
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.09141 0.07841 1.166 0.244
## ordered(PhD01).L -0.26509 0.20717 -1.280 0.201
## ordered(PhD01).Q -0.13931 0.19240 -0.724 0.469
## ordered(PhD01).C 0.13479 0.19783 0.681 0.496
## ordered(PhD01)^4 -0.02353 0.19174 -0.123 0.902
## ordered(PhD01)^5 -0.25566 0.16916 -1.511 0.131
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1514.2 on 1096 degrees of freedom
## Residual deviance: 1508.4 on 1091 degrees of freedom
## (4 observations deleted due to missingness)
## AIC: 1520.4
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = FullResYes ~ factor(PhD01), family = binomial(link = "logit"),
## data = polldatacareerstageanalysis2)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.341 -1.235 1.022 1.121 1.226
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.13525 0.11367 1.190 0.234
## factor(PhD01)2 0.06954 0.15718 0.442 0.658
## factor(PhD01)3 0.24098 0.18369 1.312 0.190
## factor(PhD01)4 -0.22487 0.20696 -1.087 0.277
## factor(PhD01)5 -0.10016 0.28830 -0.347 0.728
## factor(PhD01)6 -0.24858 0.29772 -0.835 0.404
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1514.2 on 1096 degrees of freedom
## Residual deviance: 1508.4 on 1091 degrees of freedom
## (4 observations deleted due to missingness)
## AIC: 1520.4
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = FullResYes ~ PhD01, family = binomial(link = "logit"),
## data = polldatacareerstageanalysis2)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.273 -1.253 1.085 1.103 1.177
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.26472 0.12397 2.135 0.0327 *
## PhD01 -0.04387 0.04331 -1.013 0.3111
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1514.2 on 1096 degrees of freedom
## Residual deviance: 1513.1 on 1095 degrees of freedom
## (4 observations deleted due to missingness)
## AIC: 1517.1
##
## Number of Fisher Scoring iterations: 3##
## Call:
## glm(formula = FullResYes ~ WhereLive, family = binomial(link = "logit"),
## data = polldatawhereliveanalysis2)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.311 -1.210 1.050 1.145 1.145
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.3080 0.1192 2.583 0.00981 **
## WhereLiveNorth America -0.2322 0.1408 -1.649 0.09924 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1382.6 on 1000 degrees of freedom
## Residual deviance: 1379.9 on 999 degrees of freedom
## (4 observations deleted due to missingness)
## AIC: 1383.9
##
## Number of Fisher Scoring iterations: 3##
## Call:
## glm(formula = FullResYes ~ ecoevo, family = binomial(link = "logit"),
## data = polldataecoevoanalysis2)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.266 -1.266 1.091 1.091 1.228
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.20701 0.06732 3.075 0.00211 **
## ecoevoevolution -0.32480 0.28851 -1.126 0.26026
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1298.9 on 942 degrees of freedom
## Residual deviance: 1297.6 on 941 degrees of freedom
## (2 observations deleted due to missingness)
## AIC: 1301.6
##
## Number of Fisher Scoring iterations: 3##
## Call:
## glm(formula = FullResYes ~ factor(Dept01), family = binomial(link = "logit"),
## data = polldatadepttypeanalysis2)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.331 -1.174 1.031 1.090 1.181
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.3535 0.1167 3.029 0.00245 **
## factor(Dept01)2 -0.3625 0.1506 -2.408 0.01605 *
## factor(Dept01)3 -0.1452 0.1808 -0.803 0.42202
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1321.1 on 956 degrees of freedom
## Residual deviance: 1315.1 on 954 degrees of freedom
## (3 observations deleted due to missingness)
## AIC: 1321.1
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = FullResYes ~ factor(PhD01) + WhereLive + ecoevo +
## factor(Dept01), family = binomial(link = "logit"), data = polldata)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.6845 -1.2146 0.9402 1.0989 1.4406
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.346343 0.837631 1.607 0.1080
## factor(PhD01)2 0.089420 0.162309 0.551 0.5817
## factor(PhD01)3 0.241222 0.191887 1.257 0.2087
## factor(PhD01)4 -0.215497 0.215907 -0.998 0.3182
## factor(PhD01)5 -0.087409 0.294602 -0.297 0.7667
## factor(PhD01)6 -0.267517 0.308385 -0.867 0.3857
## factor(PhD01)7 -0.008312 0.492158 -0.017 0.9865
## WhereLiveAsia -0.875818 1.014683 -0.863 0.3881
## WhereLiveAustralia -0.976865 0.865204 -1.129 0.2589
## WhereLiveEurope -0.848316 0.834541 -1.017 0.3094
## WhereLiveNorth America -1.043690 0.828131 -1.260 0.2076
## WhereLiveSouth America -0.833515 0.906331 -0.920 0.3578
## ecoevoevolution -0.340404 0.299860 -1.135 0.2563
## ecoevoother -0.207584 0.172915 -1.200 0.2299
## factor(Dept01)2 -0.347022 0.153571 -2.260 0.0238 *
## factor(Dept01)3 -0.150567 0.186054 -0.809 0.4184
## factor(Dept01)4 -0.204547 0.216299 -0.946 0.3443
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1501.8 on 1087 degrees of freedom
## Residual deviance: 1483.1 on 1071 degrees of freedom
## (34 observations deleted due to missingness)
## AIC: 1517.1
##
## Number of Fisher Scoring iterations: 4